Prognostic Value of Tumour-Associated Genes in Clear Cell Renal Cell Carcinoma
Author Information
Author(s): Tongfei Fu, Xinyi Zhang, Yuedong Liu, Junsong Wu, Xuefeng Liu, Bichao Lu, Yi Huang, Liping Yang, Yongli Zhan
Primary Institution: Guang'anmen Hospital China Academy of Chinese Medical Sciences
Hypothesis
Can single-cell RNA sequencing reveal prognostic indicators in clear cell renal cell carcinoma (ccRCC)?
Conclusion
The study developed a prognostic model that highlights the significant impact of immune cell infiltration, particularly CCL2+ neoplastic cells, on ccRCC patient prognosis.
Supporting Evidence
- The prognostic model achieved a C-index of 0.650, indicating good discrimination.
- Patients with higher proportions of CCL2+ neoplastic cells exhibited significantly higher survival rates.
- The model's predictive performance was validated across multiple datasets.
- CCL2+ neoplastic cells were more prevalent in non-responders to treatment.
Takeaway
Researchers looked at tiny parts of kidney tumors to find clues about how to treat cancer better, especially focusing on a special type of cell that can help or hurt treatment.
Methodology
The study used single-cell RNA sequencing and machine learning to analyze gene expression in ccRCC, constructing a prognostic model based on data from multiple cohorts.
Potential Biases
Potential selection bias due to reliance on public datasets.
Limitations
The study relied on public databases, which may introduce selection bias.
Participant Demographics
The study included ccRCC cases from diverse cohorts, including TCGA and ICGC.
Statistical Information
P-Value
5e-07
Statistical Significance
p<0.05
Digital Object Identifier (DOI)
Want to read the original?
Access the complete publication on the publisher's website